Getting in shape: Reconstructing three-dimensional long-track speed skating kinematics by comparing several body pose reconstruction techniques

Abstract

In gait studies body pose reconstruction (BPR) techniques have been widely explored, but no previous protocols have been developed for speed skating, while the peculiarities of the skating posture and technique do not automatically allow for the transfer of the results of those explorations to kinematic skating data. The aim of this paper is to determine the best procedure for body pose reconstruction and inverse dynamics of speed skating, and to what extend this choice influences the estimation of joint power. The results show that an eight body segment model together with a global optimization method with revolute joint in the knee and in the lumbosacral joint, while keeping the other joints spherical, would be the most realistic model to use for the inverse kinematics in speed skating. To determine joint power, this method should be combined with a least-square error method for the inverse dynamics. Reporting on the BPR technique and the inverse dynamic method is crucial to enable comparison between studies. Our data showed an underestimation of up to 74% in mean joint power when no optimization procedure was applied for BPR and an underestimation of up to 31% in mean joint power when a bottom-up inverse dynamics method was chosen instead of a least square error approach. Although these results are aimed at speed skating, reporting on the BPR procedure and the inverse dynamics method, together with setting a golden standard should be common practice in all human movement research to allow comparison between studies.

Introduction

Speed skating is, except for cycling, the fastest way for humans to propel themselves over flat land. Humans seem to have developed several skating techniques, each subjected to the one constraint that, due to the construction of the skate, there can only be a push-off lateral to the gliding direction of the blade. What the optimal technique is, has yet to be discovered. Kinetic data for biomechanical analysis are essential in this search.

A complicating factor in the biomechanical research of speed skating is the complexity of performing three-dimensional kinetic measurements on an ice rink. One skating stroke can cover a distance of 18 m, which results in a huge volume (18 m × 4 m × 2 m) in terms of motion capture. However, with the recently developed wireless instrumented klapskates (van der Kruk, den Braver, Schwab, van der Helm, & Veeger, 2016) and the rapidly improving techniques for 3D motion capture, we managed to capture 3D kinetic data of elite speed skaters for 50 m of the straight part, which implies about three to four speed skating strokes, for this project.

For a full biomechanical analysis, recorded marker positions need to be transformed into segment position and orientation. The general assumption is that the body segments are rigid. The actual marker data will however never exactly describe actual rigid bodies, due to instrumental errors and soft tissue artefacts, a well-known phenomenon (Cappozzo et al., 1997, Cappozzo et al., 1996).

Therefore, body pose reconstruction techniques (BPR) play an important role. State-of-the-art BPR technique is the global optimization method (GOM) (Lu & O’connor, 1999), which searches for the optimal pose of the multi-body system, such that the measured data points and the estimated data points from the biomechanical model are minimized in a least-square error sense. The biomechanical model can vary in model complexity e.g. number of segments and joint constraints (Andersen et al., 2010, Charlton et al., 2004, Duprey et al., 2010, Reinbolt et al., 2005).

In gait studies these techniques have been widely explored (Ojeda, Martínez-Reina, & Mayo, 2016), but no previous protocols have been developed for BPR in speed skating, while the peculiarities of the skating posture and technique do not automatically allow for the transfer of the results of those explorations to kinematic skating data. Moreover, previous studies on speed skating do not report on any of the methods used for the inverse kinematics or the inverse dynamics to determine joint power (van der Kruk et al., 2017, van der Kruk et al., 2018). It is also unclear to what extent the choice for these methods influences the joint power estimations.

The aim of this paper is to determine the best procedure for body pose reconstruction and inverse dynamics of speed skating, and to what extend this choice influences the estimation of joint power. We present an eight segment rigid body model and compare two inverse dynamics methods - bottom-up and least square error-, and four global optimization methods in terms of marker residual reduction and model fidelity - such that the joint angles obtained from the inverse kinematics meet the biomechanical restrictions of the human joints.

This paper is organized as follows; first the data collection, the body pose reconstruction techniques and the evaluation criteria are presented in the method section. Second we present the results on the marker residuals reduction and the model fidelity together with the effect of the choice of a BPR technique on the joint power estimation. Finally the results are discussed to determine the best BPR procedure for speed skating analysis.